What you’ll learn and build
A practical Data Science & AI curriculum that covers the full workflow: analyse data, train models, and deploy results. Learn in 12 weeks (full-time) or 24 weeks (part-time), with projects you can present professionally.
Foundation
SQL, Python, Jupyter Notebook, Git and GitHub, plus core maths, probability, and statistics
Data Analytics
Data analysis, preparation, visualisation, and exploratory techniques used in real projects
Classic Machine Learning
Supervised and unsupervised learning, evaluation, pipelines, and practical model improvement
Deep Learning
Neural networks, CNN architectures, optimisation, and implementation with TensorFlow and Keras
Natural Language Processing
Text processing, RNN/LSTM, attention and transformers, and building an NLP-powered chatbot
Chapter 0: Pre-Work
Data Science & AI is about working with data, making it usable, and building models that learn from it. This pre-work chapter covers core foundations so you’re ready to move confidently into analytics and Machine Learning once the bootcamp begins.
Introduction to Python
- Python Language And History
- The Basics Of Python
- Fundamental Data Structures In Python
- Classes And Objects
- Modules And Packages
- Input/Output
- Errors And Exceptions
Environments
- Python Environments
- Anaconda
- Jupyter Notebooks
SQL and Databases
- SQL Fundamentals
- SQL Queries
Linear Algebra
- Scalars And Vectors
- Matrices
- Norms
Git and GitHub
- Introduction to Version Control
- Workflow
- Inspecting Repositories
- Undoing Changes
- Fetching And Pulling Changes
- Pushing Changes
Project: Curve Fitting
- In this project you’ll tackle a classic curve-fitting task: finding the best curve equation for a dataset. Along the way, you’ll practise fundamentals like OOP, SQL, linear algebra, and the core Machine Learning workflow.
Learning Schedule
Monday to Friday, 09:30–15:30 (Europe/Athens time)
Lecture Session
09:30–11:00
Lecture Session
11:30–13:00
Hands-on Session
14:00–15:30
Our Methodology
Online Live Learning
- Join live online sessions where you can ask questions, collaborate with peers, and get feedback in real time. Cohorts work well for learners in Greece, with schedules aligned to Europe/Athens time (EET/EEST) whenever possible.
Self Study
- Part Time: 9 hours live learning + 11 hours self study (20 hours per week)
- Full Time: 22.5 hours live learning + 17.5 hours self study (40 hours per week)
Flipped Classroom Method
- Prepare with guided materials before class, then use live time for discussion, exercises, and problem-solving. This approach helps you learn actively and build confidence faster.
Guided Practice
- Expect a strong focus on doing: hands-on exercises, lab work, and portfolio projects. You’ll practise with instructor support so knowledge turns into real capability, not just theory.
Prefer to learn at your own pace?
Learn with our On-demand Data Science & AI course at your own pace with complete flexibility through our immersive, self-paced program. Master how to transform raw data into powerful insights, train intelligent models, and build real-world AI applications and graduate ready to launch your career in the world of data-driven innovation.
What You’ll Need
You don’t need a formal degree to join, but you should be ready to practise consistently and complete pre-work. If you’re in Greece and want to strengthen your analytics or AI skills, we’ll help you build solid foundations and progress to real model-building and deployment.
- Laptop or Computer: A reliable laptop or desktop computer with enough performance to run notebooks and ML tooling comfortably.
- Stable Internet Connection: Reliable internet access for live sessions, assignments, and project work.
- Basic Computer Literacy: Ability to navigate your operating system, use productivity tools, and work online.
- Basic Knowledge in Algorithmics and Programming: Basic familiarity with programming concepts (or the willingness to complete the pre-unit thoroughly) to follow the bootcamp comfortably.
- English Proficiency: B1 level or above so you can work with technical materials and participate actively (taught in English).
- Commitment to Learning: A proactive attitude toward practice, especially during pre-work, so you can keep momentum during the bootcamp.
Career Services Center
Career Development Workshops
Short, practical sessions for the CLA community, covering topics like portfolio storytelling, LinkedIn strategy, and interview prep. Join live online workshops from Greece (Europe/Athens time, EET/EEST, when possible) and get quick feedback when you need it.
Personalised Career Coaching (1:1)
Structured 1:1 sessions to clarify your direction and build a plan that fits your situation, upskilling for your current role, applying for a junior position, moving into a tech-adjacent role, or positioning yourself for a promotion.
Mock Interviews
Practice common interview formats and get actionable feedback: behavioural questions, technical discussions, how to communicate your projects, and how to handle salary expectations with professionalism and confidence.
CV & Cover Letter Reviews
Get personalised recommendations to make your CV and cover letter more focused, clearer, and more relevant to the roles you’re targeting, so recruiters can quickly understand what you can do and what you’ve built.
Job & Internship Round-Up
Curated opportunities shared by our team, with an emphasis on entry-level and junior-friendly roles. We aim to include remote options and roles relevant to Greece and the wider EU market where possible.
Career Resources Platform Access
Full access to career materials inside our platform: templates, assignments, industry resources, and step-by-step guidance to help you stay organised while you apply and improve.
Professional Guidance & Networking Events
Connect with tech professionals through online events and Career Chats. Ask questions about roles, workflows, and hiring expectations, and build a network that supports your learning journey from Greece and beyond.
Alumni Networking
Stay connected with your cohort and the wider alumni community. Share resources, discuss tools and trends, and post opportunities that might help other learners, especially those applying from Greece.
Why Choose Code Labs Academy?
1-to-1 Career Coaching
Personalised support from career specialists: CV and LinkedIn refresh, mock interviews, and a tech-focused job-search strategy.
Portfolio-Ready Projects
Graduate with a GitHub-ready portfolio of real-world projects, built in class and polished with mentor feedback.
Industry-Driven Curriculum
Curriculum refreshed every quarter to match current hiring needs in AI, cybersecurity, and web development.
Recognised Certificate
Showcase your AZAV-accredited Code Labs Academy certificate on LinkedIn, your CV, and visa applications.